# Other Compute
## What is Docker?
- Docker is a software development platform to deploy apps
- Apps are packaged in containers that can be run on any OS
- Apps run the same, regardless of where they’re run
- Any machine
- No compatibility issues
- Predictable behavior
- Less work
- Easier to maintain and deploy
- Works with any language, any OS, any technology
- Scale containers up and down very quickly (seconds)
### Where are Docker images stored?
- **Docker Hub**: Centralized public repository for storing Docker images.
- Public: Docker Hub
- Private: **Amazon ECR (Elastic Container Registry)**: AWS service for storing, managing, and deploying container images.
### Docker versus Virtual Machines
- Docker is ”sort of” a virtualization technology, but not exactly
- Resources are shared with the host => many containers on one server
| **Docker Containers** | **Virtual Machines (VMs)** |
| -------------------------------------- | ----------------------------------------- |
| Lightweight, shares the host OS kernel | Heavier, includes full OS |
| Starts in seconds | Slower startup (minutes) |
| Portable, fast scaling | Not as portable, more resource-intensive |
| Best for microservices & modern apps | Best for running multiple OS environments |
## ECS (Elastic Container Service)
- Fully managed container orchestration service.
- Supports Docker containers.
- Launch Docker containers on AWS
- AWS takes care of starting / stopping containers
- **Two launch modes**: **EC2** (self-managed instances) and **Fargate** (serverless).
- Provides integration with IAM, VPC, ELB, and ECR.
## Fargate
- Serverless compute engine for containers, works with ECS and EKS.
- No need to manage EC2 instances.
- Pay for resources used (vCPU and memory).
- AWS just runs containers for you based on the CPU / RAM you need
## ECR (Elastic Container Registry)
- Fully managed Docker container registry.
- Stores, manages, and secures Docker images.
- Integrated with **ECS**, **EKS**, and **Fargate** for easy deployment.
- This is where you store your Docker images so they can be run by ECS or Fargate
## What’s Serverless?
- No need to provision, scale, or manage servers.
- Resources are automatically provisioned and scaled by AWS.
- Serverless is a new paradigm in which the developers don’t have to manage servers anymore…
- They just deploy code
- They just deploy… functions !
- Initially... Serverless == FaaS (Function as a Service)
- Serverless was pioneered by AWS Lambda but now also includes anything that’s managed: “databases, messaging, storage, etc.”
- Serverless does not mean there are no servers…
- it means you just don’t manage / provision / see them
- Ideal for event-driven and stateless applications.
## Why AWS Lambda?
- Serverless compute service to run code without managing infrastructure.
- Executes code in response to events (e.g., API calls, file uploads).
- Scales automatically and you only pay for usage.
| EC2 | Lambda |
| -------------------------------------------------- | ----------------------------------------- |
| Virtual Servers in the Cloud | Virtual functions – no servers to manage! |
| Limited by RAM and CPU | Limited by time - short executions |
| Continuously running | Run on-demand |
| Scaling means intervention to add / remove servers | Scaling is automated! |
### Benefits of AWS Lambda
- **No server management**: AWS handles the infrastructure.
- **Automatic scaling**: Scales based on event triggers.
- **Flexible scaling**: Runs from a few requests per day to thousands per second.
- **Event-driven architecture**: Ideal for apps that need to respond to events.
- Easy Pricing:
- Pay per request and compute time
- Free tier of 1,000,000 AWS Lambda requests and 400,000 GBs of compute time
- Integrated with the whole AWS suite of services
- Event-Driven: functions get invoked by AWS when needed
- Integrated with many programming languages
- Easy monitoring through AWS CloudWatch
- Easy to get more resources per functions (up to 10GB of RAM!)
- Increasing RAM will also improve CPU and network!
### AWS Lambda Language Support
- Node.js
- Python
- Ruby
- Java
- Go
- .NET Core
- custom runtime (via container images) (community supported, example Rust)
- Lambda Container Image
- The container image must implement the Lambda Runtime API
- ECS / Fargate is preferred for running arbitrary Docker images
### AWS Lambda Pricing: Example
- Based on number of requests and execution time.
- You can find overall pricing information here:
- First **1 million requests/month** are free.
- After that, **$0.20 per million requests**.
- **Execution duration**: $0.00001667 for every GB-second used (first 400,000 GB-seconds free per month).
- - Pay per duration: (in increment of 1 ms)
- 400,000 GB-seconds of compute time per month for FREE
- == 400,000 seconds if function is 1GB RAM
- == 3,200,000 seconds if function is 128 MB RAM
- After that $1.00 for 600,000 GB-seconds
- It is usually **very cheap** to run AWS Lambda so it’s **very popular**
## Amazon API Gateway
- Managed service for creating, publishing, and monitoring REST, HTTP, and WebSocket APIs.
- Integrates with AWS Lambda for fully serverless APIs.
- Serverless and scalable
- Support for security, user authentication, API throttling, API keys, monitoring.
- **Throttling**, **caching**, and **authorization** features built-in.
## AWS Batch
- Fully managed service for running batch processing workloads.
- Dynamically provisions compute resources based on job requirements.
- Suitable for large-scale data processing, such as machine learning and rendering tasks.
- Efficiently run 100,000s of computing batch jobs on AWS
- A “batch” job is a job with a start and an end (opposed to continuous)
- Batch will dynamically launch EC2 instances or Spot Instances
- AWS Batch provisions the right amount of compute / memory
- You submit or schedule batch jobs and AWS Batch does the rest!
- Batch jobs are defined as Docker images and run on ECS
- Helpful for cost optimizations and focusing less on the infrastructure
## Batch vs Lambda
| **AWS Batch** | **AWS Lambda** |
| ------------------------------------------- | ------------------------------------------ |
| Designed for **batch processing** | Designed for **event-driven** architecture |
| Handles large-scale compute jobs | Executes short-lived functions |
| Custom EC2 instances or Fargate tasks | Fully serverless, no server management |
| Jobs may take minutes to hours | Max execution time of 15 minutes |
| Rely on EBS / instance store for disk space | Limited temporary disk space |
## Amazon Lightsail
- Virtual servers, storage, databases, and networking
- Low & predictable pricing
- Simpler alternative to using EC2, RDS, ELB, EBS, Route 53…
- Great for people with little cloud experience!
- Can setup notifications and monitoring of your Lightsail resources
- Use cases:
- Simple web applications (has templates for LAMP, Nginx, MEAN, Node.js…)
- Websites (templates for WordPress, Magento, Plesk, Joomla)
- Dev / Test environment
- Has high availability but no auto-scaling, limited AWS integrations
## Lambda Summary
- Lambda is Serverless, Function as a Service, seamless scaling, reactive
- Lambda Billing:
- By the time run x by the RAM provisioned
- By the number of invocations
- Language Support: many programming languages except (arbitrary) Docker
- Invocation time: up to 15 minutes
- Use cases:
- Create Thumbnails for images uploaded onto S3
- Run a Serverless cron job
- API Gateway: expose Lambda functions as HTTP API
## Other Compute Summary
- Docker: container technology to run applications
- ECS: run Docker containers on EC2 instances
- Fargate:
- Run Docker containers without provisioning the infrastructure
- Serverless offering (no EC2 instances)
- ECR: Private Docker Images Repository
- Batch: run batch jobs on AWS across managed EC2 instances
- Lightsail: predictable & low pricing for simple application & DB stacks